Integrating dynamic modeling and continuous cultivation to enhance recombinant β-glucosidase production in Komagataella phaffii

Cultivation under hypothermia has emerged as an interesting strategy for enhancing recombinant protein production in Komagataella phaffii , yet predictive approaches capable of integrating the effects of temperature and cell growth rate for rational bioprocess optimization remain limited. In this work, we investigated the influence of cultivation temperature on recombinant β-glucosidase (BGL1) production in the hybrid K. phaffii strain S467 by combining bioprocess characterization with dynamic mathematical modeling. Batch cultures performed at 20, 25 and 30 °C showed that hypothermia increased recombinant protein secretion while reducing biomass formation, revealing a trade-off between cell growth and product formation. To quantitatively describe these dynamics, a Droop-based model incorporating delayed coupling between substrate uptake and biomass synthesis was fitted using the experimental data. Model simulations predicted that continuous cultivation at 20 °C and a dilution rate of 0.045 h −1 maximized the total secreted protein volumetric productivity. Chemostat experiments at selected conditions yielded biomass concentrations and total secreted protein productivities close to the simulated values, supporting the model-predicted trends and its potential as a tool for process optimization. Interestingly, the highest specific BGL1 activity was observed at the highest dilution rate despite a lower bgl1 transcript level and secreted protein production, suggesting that cultivation conditions influence recombinant protein traits through mechanisms beyond transcriptional regulation. Collectively, these results show that integrating experimental bioprocess characterization, predictive dynamic modeling and targeted molecular analyses provide an effective framework for rational optimization of recombinant protein production in this biotechnologically relevant yeast.